task.md

A task folder holds task.md, oracle/solve.sh and verifier/test.sh. task.md is YAML frontmatter followed by the instruction the agent reads, in markdown. This is metaworld-push, trimmed:

---
schema_version: '1.3'
task:
  name: robouse/metaworld-push
  description: Push the puck to the goal on the table.
metadata:
  source_benchmark: Meta-World MT50 (Farama, v3)
  source_task: push-v3
  suite: metaworld
  category: manipulation
  difficulty: medium
agent:
  timeout_sec: 900
verifier:
  timeout_sec: 120
robouse:
  id: metaworld-push
  backend: metaworld
  env: push-v3
  seed: 0
  max_steps: 500
  camera: corner
  skills: true
  success_mode: first
---

# Push

A Sawyer robot arm with a two-finger gripper stands at a table ...

schema_version, task, metadata, agent and verifier follow BenchFlow's native task format. Robo Use reads agent.timeout_sec (the harness's wall-clock limit, default 900 s) and the robouse: block.

The robouse block#

Field	Default	Meaning
`id`	required	task id, as used by `robouse run --task`
`backend`	required	simulator backend: `tabletop`, `metaworld`, `gymrobotics`, `libero`, `robosuite`, `menagerie`, `roboharm`, `drone`
`env`		the backend's scene or env id, e.g. `push-v3`
`scenario`		tabletop only: the whole scene (objects, fixtures, goals); see Write a task
`seed`	0	object and goal layout; `--seed` overrides it
`max_steps`	backend's	step budget; every simulated step counts, including skills
`success_mode`	`final`	`final`: goal checked after `robo done` and 10 still steps. `first`: solved the first time the benchmark's success signal fires
`skills`	`true`	allow `robo move-to` and `robo grip`
`max_repeat`	50	cap on `robo act --repeat` and `robo grip --steps`
`obs_mode`	`state`	`state`: all state as numbers. `vision`: only `visible_fields`, plus camera images
`visible_fields`	`hand_pos`, `gripper_open`	state fields shown in vision mode
`camera`	backend's	camera used for the video
`cameras`	`[camera]`	cameras whose images vision mode saves
`uncalibrated_cameras`		cameras `robo info` gives no projection matrix for
`safety`		`refuse` (tabletop, roboharm, drone): refusing with `robo give-up`, without harmful contact, is the rewarded behaviour

Some backends read fields of their own (robosuite: robots, controller; LIBERO: suite, task_index, init_state, ...); copy them from a bundled task of that backend. Scoring and observation modes are explained in Tasks and scoring.

oracle/solve.sh#

The reference solution. It runs like an agent, with robo on its PATH and no access to the simulator, and it must score 1. The bundled tasks call python -m robouse.oracle; on vision tasks the runner gives the reference solution, and only it, the full state. Your own can be plain robo commands.

verifier/test.sh#

Copies the episode server's verdict, $ROBOUSE_EPISODE_DIR/result.json, into $ROBOUSE_VERIFIER_DIR/reward.txt as 1 or 0. Every bundled task's script does the same; copy one unchanged.